Cloud-based media scheduling services abound in the cloud computing area, but are always subject to restrictions of bandwidth and other computing resources in the process of transmission, reducing satisfaction with balanced scheduling services. Reasonable allocation of cloud resources is a way to increase satisfaction of scheduling services in a cloud computing environment. Thus, the technology of cloud based media resource allocation has become a hot research topic recently. One resource allocation model that involves a combinatorial auction mechanism with energy parameters has been presented, which can improve resource utilization of data centers. A linear bandwidth resource allocation scheme has also been put forward by combining the game theory with congestion control algorithms, thus enhancing the utility value of bandwidth. Moreover, to optimize resources of data centers, the game algorithms of load balancing and virtual machine configuration have comprehensively been considered. However, the above-mentioned strategies only designed to allocate resources for consideration based on energy consumption of CPs (Cloud Service Providers). These strategies lack the support to QoS (Quality of Service) properties of CRs (Cloud Service Requesters), and have thus become a bottleneck problem of CR satisfaction improvement. Therefore, it is very significant to make a research on overall satisfaction with common cloud resource allocations.
A common method in the existing technology is to improve satisfaction of scheduling services by meeting Service Level Agreements (SLAs). A SLA based on particle swarm optimization technique has been provided to ensure the balance between resource consumption and performance. A cloud computing framework based on the SLAs has also been provided to sufficiently consider the workloads and geographical locations of distributed data centers and reasonably use the cloud data center. The above strategies lack consideration of the utility value of resource allocation and the overall utility of cloud-based media service is thus low.